Zurück zu Mathematical Thinking in Computer Science

Sterne

1,819 Bewertungen

•

425 Bewertungen

Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. In this course, we will learn the most important tools used in discrete mathematics: induction, recursion, logic, invariants, examples, optimality. We will use these tools to answer typical programming questions like: How can we be certain a solution exists? Am I sure my program computes the optimal answer? Do each of these objects meet the given requirements?
In the course, we use a try-this-before-we-explain-everything approach: you will be solving many interactive (and mobile friendly) puzzles that were carefully designed to allow you to invent many of the important ideas and concepts yourself.
Prerequisites:
1. We assume only basic math (e.g., we expect you to know what is a square or how to add fractions), common sense and curiosity.
2. Basic programming knowledge is necessary as some quizzes require programming in Python....

AD

25. März 2019

The teachers are informative and good. They explain the topic in a way that we can easily understand. The slides provide all the information that is needed. The external tools are fun and informative.

AM

27. Feb. 2021

It is a great course! teachers explain everything with care. While providing lectures there are some popup ques that verify whether you understood that lecture or not. Overall, a great experience.

Filtern nach:

von Mohammed R

•30. Apr. 2019

Absloutely Fantastic. I highly recommend it to anyone who wants to learn data structures and algorithms thoroughly.

von Saikat M

•2. Jan. 2018

Enjoyable and interesting...also easy to follow for people like me who have been out of college long time back.

von Ernest D

•5. Jan. 2019

this is a very nice course ,its has broaden my whole knowledge about maths

thanks to the creator of this course

von HAILEMICHAEL Y M

•12. Okt. 2019

The course is very good at equipping the basic math concepts for computer science. I highly recommend it!

von Swarnava S

•13. Juni 2019

Awesome course for beginners. It helped me alot to understand the logic and how to solve problems.

von Rafael D d L P

•2. Aug. 2018

Great introduction to mathematical thinking and how to apply it to computational problems.

von KUMAR A

•24. Jan. 2020

This was the one-stop that I'll never regret learning things again in a different manner.

von Vishnu M

•7. Sep. 2019

Puzzles are great. Seems Instructors put lots of efforts into it. Different approach !

von Jesse W

•2. Mai 2019

This course mostly consists of a set of loosely related under the umbrella of discrete mathematics. A lot of the exercises take the form of puzzles where you either have to solve the puzzle or determine whether a solution is impossible. The puzzles are fun and make for good brain exercise; however, I'm not sure if all of this has made me a better programmer. It's worth noting that most Computer Science degrees will require some form of discrete math coursework, so if you're considering CS and are worried about the math requirements, this Specialization would be good to try out.

von Anton M

•4. Apr. 2019

Great course with variety of different mathematical puzzles.

Two things can be improved:

1) It's not always obvious which global subject is discussed during the week and what is a connection with puzzles, some kind of review video at start of each week will be helpful.

2) Sometimes explanations not clear at all. I did watched some videos 2-3 times before completely understand what is going on. It will be great to have a rigours proof of theorems as supplementary reading material.

von Mike P

•31. Jan. 2019

I liked the course, and I enjoyed the math for sure. BUT, I think there were some sections that could have been explained more thoroughly and perhaps some videos that could have been shot again to be more clear. But whatever, I am very grateful to be able to learn this here :)

von Vladimir K

•5. Feb. 2018

While the material itself is important and very useful in general, the course, unfortunately, doesn't have enough practical material to help students to internalise it.

von Frederick H K K

•21. Jan. 2019

Some explanation are unclear or confusing.

von Md. Z M

•26. Apr. 2019

The course is taught by 3 instructors. This makes the experience strikingly unbalanced. The style of course delivery and explanation is very poor with one of the instructors, the one who took Week 1 and 6. The rest of the weeks were OK. The other two instructors were clear with their arguments. This course has a very different approach (do-it-yourself-before-expalnation-by-instructors), although it was mentioned clearly on the Course Info page. If you can make out yourself what strategy to apply for the interactive puzzles, then you are doing good. Otherwise, the puzzles will just be trial-and-error games for you. The instructors were kind enough to answer on the Discussion Forum, but do not expect much activity from your fellow learners as there might be very few people taking this course with you.

von Carlos V

•15. Feb. 2020

I believe that the content of this course is both important and interesting. However, the learning methods used are awful. To begin with, while going through the interactive puzzles I felt that I was not learning anything related to the core lesson at hand. Moreover, the exercises feel like disconnected trivia unrelated to the theoretical explanations. I think the course should be heavily revamped in order to present a proper and useful corpus of knowledge.

von Himanshu P M

•7. Mai 2020

This course is good for beginner.

rather than being complicated it will change the way you think.

one advice---- you should have knowledge of python basic to complete the assignment of this course

von yonas a

•24. Mai 2020

I have come to know how mathematical proof is fun thing to do, this course transformed me, i highly recommend it to every one. I would like to thank every one involved in providing this course.

von Mohamed A H

•26. Juni 2020

This course will improve your problem solving skills and gives you a rigorous explanation in how to counter various mathematical problems in the real life. You will think like a mathematician.

von Jonibek N

•29. Apr. 2020

Course was good, but sometimes i needed additional sources to understand topic better. Maybe, it was because of my english. Anyway it gave me a path what i should look for! Thank you!

von Sanjay A

•17. Sep. 2017

I was waiting for such a great course on discrete Mathematics in coursera.

Thank you UC San Diego

von Dmytro N

•5. Okt. 2017

I like the course. Still some mistakes and bugs, but course is really interesting to pass. Thanks

von PLN R

•9. Juli 2019

An amazing course really!! The interactive fun assignments make it all the more interesting!! :D

von Eddy P

•22. Sep. 2018

There are many very interesting cases in this course! I will definitely recommend it to others!

von Andrew M

•26. Okt. 2017

A great introductory course and well organized. You can feel that professor loves mathematics.

von Anup K K

•27. Apr. 2020

Just the last Bonus Track problem please give some hints how to approach and solve the problem

- Sinn und Zweck im Leben finden
- Medizinische Forschung verstehen
- Japanisch für Anfänger
- Einführung in Cloud Computing
- Grundlagen der Achtsamkeit
- Grundlagen des Finanzwesens
- Maschinelles Lernen
- Maschinelles Lernen mittels Sas Viya
- Die Wissenschaft des Wohlbefindens
- Contact-Tracing im Kontext von COVID-19
- KI für alle
- Finanzmärkte
- Einführung in die Psychologie
- Erste Schritte mit AWS
- Internationales Marketing
- C++
- Predictive Analytics und Data-Mining
- UCSD: Learning How to Learn
- Michigan: Programming for Everybody
- JHU: R-Programmierung
- Google CBRS CPI Training

- Natural Language Processing (NLP)
- KI für Medizin
- Guter Umgang mit Worten: Redaktionelles Schreiben
- Modellbildung von Infektionskrankheiten
- Die Aussprache des US-amerikanischen Englisch
- Software-Testautomatisierung
- Deep Learning
- Python für alle
- Data Science
- Geschäftsgründungen
- Excel-Kenntnisse für Beruf
- Data Science mit Python
- Finance for Everyone
- Kommunikationsfähigkeiten für Ingenieure
- Verkaufstraining
- Career Brand Management
- Wharton: Unternehmensanalytik
- Penn: Positive Psychology
- Washington: Maschinelles Lernen
- CalArts: Grafikdesign

- Zertifikate über berufliche Qualifikation
- MasterTrack-Zertifizierungen
- Google IT-Support
- IBM Datenverarbeitung
- Google Cloud Data Engineering
- IBM Applied AI
- Google Cloud Architecture
- IBM Cybersecurity Analyst
- Google IT Automation with Python
- IBM z/OS Mainframe Practitioner
- UCI: Angewandtes Projektmanagement
- Zertifizierung in Instructional Design
- Zertifizierung in Bauwesen und -management
- Zertifizierung in Big Data
- Zertifizierung Maschinelles Lernen für Analytics
- Zertifizierung in Innovation Management & Entrepreneurship
- Zertifizierung in Nachhaltigkeit und Entwicklung
- Zertifizierung in Soziale Arbeit
- Zertifizierung KI und maschinelles Lernen

- Abschlüsse in Informatik
- Business-Abschlüsse
- Abschlüsse im Gesundheitswesen
- Abschlüsse in Data Science
- Bachelorabschlüsse
- Bachelor of Computer Science
- MS Elektrotechnik
- Bachelor Completion Degree
- MS Management
- MS Informatik
- MPH
- Master-Abschluss in Buchhaltung
- MCIT
- MBA online
- Master of Applied Data Science
- Global MBA
- Master in Innovation & Entrepreneurship
- MCS Data Science
- Master in Informatik
- Master-Abschluss in Public Health